A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...

(a) An illustrative map for Crack-Net, including the initial features, looping solver for data generation, model training, and prediction performance. (b) The Crack-Net architecture, which utilizes ...

Traffic classification is a crucial task for network security. One of the most difficult challenges is to accurately identify the traffic of unknown applications as well as discriminate the known ...

Shivik Labs unveils TRIDENT, an advanced AI reasoning framework, significantly improving large language models' performance ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...